1. Field of the Invention
The present invention relates to video surveillance systems in general, and to an apparatus and methods for the automatic real-time detection of abnormal motion in video streams, in particular.
2. Discussion of the Related Art
Video surveillance is commonly recognized as a critical security tool. Human operators provide the key for detecting security breaches by watching surveillance screens and facilitating immediate response. However, operators face an overload of information, watching multiple cameras on split screens, and since most of the time nothing happens, they often lose focus, get tired and bored. This results in operational inefficiency, often known as “the monitoring syndrome” whereby security infractions are usually detected only after they occur. Moreover, recorded video data is hard to locate and tedious to access and review, so it is seldom used.
For many transportation sites like airports, subways and highways, as well as for other facilities like large corporate buildings, financial institutes, correctional facilities and casinos where security and control plays a major role, video surveillance systems implemented by CCTV and IP cameras are a major and critical tool. A typical site can have one or more and in some cases tens, hundreds and even thousands of cameras all around, connected to the control room for monitoring and some times also for recording. The number of monitors in the control room is usually much smaller than the number of cameras, while the number of human eyes watching these monitors is smaller yet. Recent military tests have demonstrated that after approximately 12 minutes of continuous viewing of two or more sequencing monitors, an operator will miss up to 45% of scene activity, while after 22 minutes, an operator will miss up to 95% of scene activity.
When trying to investigate an event using video recordings from a specific camera and other related cameras, it is usually not practical to watch the entire recorded footage available. The ability to discriminate between normal and abnormal motion in video sequences can be a key factor for such applications. There is great need for a mechanism that can automatically alert the operator and direct his or her attention to unusual activity in one of the monitored scenes, as well as to summarize the important events in video recordings, thus dramatically shorten the investigation process.